mlsanityData to 13 Oct 2026

Children's Mental Models of AI Reasoning: Implications for AI Literacy Education

arXiv 2505.16031 ↗First posted 21 May 2025cs.AI cs.HCcited by 5

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

As artificial intelligence (AI) advances in reasoning capabilities, most recently with the emergence of Large Reasoning Models (LRMs), understanding how children conceptualize AI's reasoning processes becomes critical for fostering AI literacy. While one of the "Five Big Ideas" in AI education highlights reasoning algorithms as central to AI decision-making, less is known about children's mental models in this area. Through a two-phase approach, consisting of a co-design session with 8 children followed by a field study with 106 children (grades 3-8), we identified three models of AI reasoning: Deductive, Inductive, and Inherent. Our findings reveal that younger children (grades 3-5) often attribute AI's reasoning to inherent intelligence, while older children (grades 6-8) recognize AI as a pattern recognizer. We highlight three tensions that surfaced in children's understanding of AI reasoning and conclude with implications for scaffolding AI curricula and designing explainable AI tools.

Key facts. Cited by 5 papers in the map (data through 13 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 13 of its 106 references that are in the map. First posted on arXiv 21 May 2025.

Builds on

13 of 106 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025Reasoning Language Models: A Blueprint20 Jan
  2. 2022Towards Reasoning in Large Language Models: A Survey20 Dec

Other references · 11

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,979
  2. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,181
  3. 2023The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domaincited by 99
  4. 2020Human Factors in Model Interpretability: Industry Practices, Challenges, and Needscited by 73
  5. 2024OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AIcited by 70
  6. 2024From Explainable to Interactive AI: A Literature Review on Current Trends in Human-AI Interactioncited by 26
  7. 2023"Alexa doesn't have that many feelings": Children's understanding of AI through interactions with smart speakers in their homescited by 8
  8. 2021"Alexa, Can I Program You?": Student Perceptions of Conversational Artificial Intelligence Before and After Programming Alexacited by 6
  9. 2024Dataset Scale and Societal Consistency Mediate Facial Impression Bias in Vision-Language AIcited by 4
  10. 2024Representation Bias of Adolescents in AI: A Bilingual, Bicultural Studycited by 4
  11. 2019Using Scratch to Teach Undergraduate Students' Skills on Artificial Intelligencecited by 3

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2026: 5.

5 papers.

  1. 2026What is Safety? Corporate Discourse, Power, and the Politics of Generative AI Safetycited by 1
  2. 2026Toys that listen, talk, and play: Understanding Children's Sensemaking and Interactions with AI Toyscited by 1
  3. 2026A Privacy by Design Framework for Large Language Model-Based Applications for Childrencited by 0
  4. 2026AI Hallucination from Students' Perspective: A Thematic Analysiscited by 0
  5. 2026Where Does AI Leave a Footprint? Children's Reasoning About AI's Environmental Costscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025A Structured Unplugged Approach for Foundational AI Literacy in Primary Education
  2. 2026Rethinking Generative AI Literacy: An Integrative, Developmental, and Dialectical Framework for K-12 Teacher Education
  3. 2025Learning to Use AI for Learning: Teaching Responsible Use of AI Chatbot to K-12 Students Through an AI Literacy Module
  4. 2025Probing the "Psyche'' of Large Reasoning Models: Understanding Through a Human Lens
  5. 2024Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads
  6. 2025World Models in Artificial Intelligence: Sensing, Learning, and Reasoning Like a Child
  7. 2026The Impact of AI Usage and Informativeness on Skill Development in Logical Reasoning
  8. 2023Comparing Machines and Children: Using Developmental Psychology Experiments to Assess the Strengths and Weaknesses of LaMDA Responses